Estimation of chlorophyll content in intertidal mangrove leaves with different thicknesses using hyperspectral data

doi:10.1016/j.ecolind.2019.105511

	Estimation of chlorophyll content in intertidal mangrove leaves with different thicknesses using hyperspectral data
	Zhao, Yunxia 1; Yan, Chunhua 1; Lu, Shan 2; Wang, Pei3 ; Qiu, Guo Yu 1; Li, Ruili 1
刊名	ECOLOGICAL INDICATORS
	2019-11-01
卷号	106 页码:13
关键词	Leaf surfaces Hyperspectral reflectance Leaf chlorophyll content Leaf thickness Mangrove The modified Datt index
ISSN号	1470-160X
DOI	10.1016/j.ecolind.2019.105511
通讯作者	Li, Ruili(liruili@pkusz.edu.cn)
英文摘要	Mangrove forests worldwide are mostly degrading and the degradation can be monitored by the leaf chlorophyll (Chl) content, which can be estimated from a quick non-destructive remote measurement. Although there are extensive studies on spectrometric remote sensing methods, few studies on intertidal mangroves are available, and the non-destructive Chl content monitoring method for mangrove with unique leaf characteristics has not been proposed. To develop a valid, non-destructive method for Chl estimation, this study examined nine commonly used vegetation indexes (VIs) for both adaxial and abaxial leaf surfaces of four mangrove species with different leaf thicknesses. Results showed that the modified Datt index (MDATT) was the most effective for estimating the Chl content for both leaf surfaces of various species. An improved MDATT index (IMDATT), in the form of (R-527-R-746)/(R-527-R-747), performed best with r = -0.88 and RMSE = 8.70 mu g/cm(2), among all the optimal VIs tested, and proved to be applicable to monitor Chl content with low sensitivity to the variations of leaf surfaces. It proved to be applicable to monitor Chl content in the validation data sets of all species (r = 0.87 and RMSE = 8.20 mu g/cm(2)) and it could be more effective for specific species, with larger r and smaller RMSE. In addition, the different performances of IMDATT could be attributed to the species, as well as the leaf thickness. In conclusion, IMDATT could be broadly applicable to intertidal mangrove plants, especially for species with thin leaves. The research provides a robust tool for monitoring mangrove Chl content.
资助项目	Program of Science and Technology of Shenzhen[JSGG20170413103811649] ; Program of Science and Technology of Shenzhen[JCYJ20160330095549229] ; Program of Science and Technology of Guangdong Province ; Special fund of State Key Joint Laboratory of Environment Simulation and Pollution Control[18K05ESPCP]
WOS关键词	LEAF CHLOROPHYLL ; SPECTRAL REFLECTANCE ; RED EDGE ; INFRARED REFLECTANCE ; FOLIAR CHLOROPHYLL ; VEGETATION INDEXES ; REMOTE ESTIMATION ; SHENZHEN BAY ; FOREST ; ABSORPTION
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000490577900075
资助机构	Program of Science and Technology of Shenzhen ; Program of Science and Technology of Guangdong Province ; Special fund of State Key Joint Laboratory of Environment Simulation and Pollution Control
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/26675]
专题	中国科学院自动化研究所
通讯作者	Li, Ruili
作者单位	1.Peking Univ, Shenzhen Key Lab Heavy Met Pollut Control & Reuti, Sch Environm & Energy, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China 2.Northeast Normal Univ, Sch Geog Sci, 5268 Renmin St, Changchun 130024, Jilin, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Yunxia,Yan, Chunhua,Lu, Shan,et al. Estimation of chlorophyll content in intertidal mangrove leaves with different thicknesses using hyperspectral data[J]. ECOLOGICAL INDICATORS,2019,106:13.
APA	Zhao, Yunxia,Yan, Chunhua,Lu, Shan,Wang, Pei,Qiu, Guo Yu,&Li, Ruili.(2019).Estimation of chlorophyll content in intertidal mangrove leaves with different thicknesses using hyperspectral data.ECOLOGICAL INDICATORS,106,13.
MLA	Zhao, Yunxia,et al."Estimation of chlorophyll content in intertidal mangrove leaves with different thicknesses using hyperspectral data".ECOLOGICAL INDICATORS 106(2019):13.